{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {
    "colab_type": "text",
    "id": "view-in-github"
   },
   "source": [
    "<a href=\"https://colab.research.google.com/github/jermwatt/machine_learning_refined/blob/main/notes/13_Multilayer_perceptrons/13_5_Activation.ipynb\" target=\"_parent\"><img src=\"https://colab.research.google.com/assets/colab-badge.svg\" alt=\"Open In Colab\"/></a>"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "id": "rqq4TEFseUph"
   },
   "source": [
    "## Chapter 13: Multi-layer Perceptrons "
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "This notebook contains interactive content from an early draft of the university textbook <a href=\"https://github.com/neonwatty/machine-learning-refined/tree/main\">\n",
    "Machine Learning Refined (2nd edition) </a>.\n",
    "\n",
    "The final draft significantly expands on this content and is available for <a href=\"https://github.com/neonwatty/machine-learning-refined/tree/main/chapter_pdfs\"> download as a PDF here</a>."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "id": "bChbTpIGeUpi"
   },
   "source": [
    "# 13.5 Activation functions"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "id": "NZPjehG6eUpi"
   },
   "source": [
    "In principle one can use any function as an activation for a multi-layer perceptron. For some time after their invention activations were chosen largely based on their biological plausibility, since this is the perspective in which neural networks themselves were largely regarded (as briefly detailed in Section 13.1.5). However these original biologically motivated activations presented serious technical challenges to properly optimizing models employing multi-layer perceptrons. Today activation functions are chosen based on practical considerations like our ability to properly optimize multi-layer perceptron models which employ them as well as (of course) the general performance they provide. In this Section we briefly review popular historical and modern activation functions. "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {
    "id": "2gfBkocSeUpj"
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Requirement already satisfied: github-clone in /Users/jeremywatt/Desktop/machine-learning-refined/venv/lib/python3.10/site-packages (1.2.0)\n",
      "Requirement already satisfied: requests>=2.20.0 in /Users/jeremywatt/Desktop/machine-learning-refined/venv/lib/python3.10/site-packages (from github-clone) (2.32.3)\n",
      "Requirement already satisfied: docopt>=0.6.2 in /Users/jeremywatt/Desktop/machine-learning-refined/venv/lib/python3.10/site-packages (from github-clone) (0.6.2)\n",
      "Requirement already satisfied: charset-normalizer<4,>=2 in /Users/jeremywatt/Desktop/machine-learning-refined/venv/lib/python3.10/site-packages (from requests>=2.20.0->github-clone) (3.4.0)\n",
      "Requirement already satisfied: idna<4,>=2.5 in /Users/jeremywatt/Desktop/machine-learning-refined/venv/lib/python3.10/site-packages (from requests>=2.20.0->github-clone) (3.10)\n",
      "Requirement already satisfied: urllib3<3,>=1.21.1 in /Users/jeremywatt/Desktop/machine-learning-refined/venv/lib/python3.10/site-packages (from requests>=2.20.0->github-clone) (2.2.3)\n",
      "Requirement already satisfied: certifi>=2017.4.17 in /Users/jeremywatt/Desktop/machine-learning-refined/venv/lib/python3.10/site-packages (from requests>=2.20.0->github-clone) (2024.12.14)\n",
      "\n",
      "\u001b[1m[\u001b[0m\u001b[34;49mnotice\u001b[0m\u001b[1;39;49m]\u001b[0m\u001b[39;49m A new release of pip is available: \u001b[0m\u001b[31;49m24.2\u001b[0m\u001b[39;49m -> \u001b[0m\u001b[32;49m24.3.1\u001b[0m\n",
      "\u001b[1m[\u001b[0m\u001b[34;49mnotice\u001b[0m\u001b[1;39;49m]\u001b[0m\u001b[39;49m To update, run: \u001b[0m\u001b[32;49mpip install --upgrade pip\u001b[0m\n",
      "chapter_13_images already cloned!\n"
     ]
    }
   ],
   "source": [
    "# install github clone - allows for easy cloning of subdirectories\n",
    "!pip install github-clone\n",
    "from pathlib import Path \n",
    "\n",
    "# clone images\n",
    "if not Path('chapter_13_images').is_dir():\n",
    "    !ghclone https://github.com/neonwatty/machine-learning-refined-notes-assets/tree/main/notes/13_Multilayer_perceptrons/chapter_13_images\n",
    "else:\n",
    "    print('chapter_13_images already cloned!')\n",
    "        \n",
    "\n",
    "# import autograd functionality to bulid function's properly for optimizers\n",
    "import autograd.numpy as np\n",
    "from autograd import grad\n",
    "import matplotlib.pyplot as plt\n",
    "from matplotlib import gridspec\n",
    "import IPython, copy\n",
    "from IPython.display import Image, HTML\n",
    "\n",
    "# image paths\n",
    "image_path_1 = \"chapter_13_images/maxout.png\"\n",
    "\n",
    "# this is needed to compensate for %matplotlib notebook's tendancy to blow up images when plotted inline\n",
    "%matplotlib inline\n",
    "from matplotlib import rcParams\n",
    "rcParams['figure.autolayout'] = True\n",
    "\n",
    "%load_ext autoreload\n",
    "%autoreload 2"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "id": "F3FMvSsAeUpr"
   },
   "source": [
    "#### <span style=\"color:#a50e3e;\">Example 1. </span>  The step and sigmoid activations"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "id": "TqrrI4NHeUpr"
   },
   "source": [
    "As broadly discussed in Section 13.1.5 the concept of neural networks was first introduced from a biological perspective where each unit of an architecture mimics a neuron in the human brain. Such neurons were thought to act somewhat like digital switches, being either completely 'on' or 'off' to transmitting information to connected cells. This belief naturally led to the use of a *step function* taking on just two values: $0$ (off) and $1$ (on). However this kind of step function (which we discuss in the context of logistic regression in Section 6.1) leads to piece-wise flat cost functions (like the one shown in Example 2 of Section 6.1) which are extremely difficult to optimize using any local optimization technique. In the context of logistic regression this sort of problem is what led to the *logistic sigmoid* introduced in Section 6.1.3. For the same reason the sigmoid function was one of the first popularly used activation functions. "
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "id": "9g1pam1ReUpr"
   },
   "source": [
    "As a smooth approximation to the step function, the logistic sigmoid was viewed as a reasonable compromise between the desired neuronal model and the practical need to tune parameters properly. While the sigmoid performs very well in the comparatively simpler context of linear classification, when used as an activation function it often leads to a technical issue known as the *vanishing gradient* problem. \n",
    "If we examine the derivative of a single-input sigmoid, as shown in the bottom left panel of Figure below, we can see that any large (negative or positive) value passed through the derivative of the sigmoid is mapped to a value near zero. When used as activation in a multi-layer perceptron this potential problem can synergize across its presence in many units and layers, particularly when normalization schemes are not employed, and cause the gradient of a model employing such a network to *vanish* unexpectedly. This can prematurely halt the progress of first order optimizers, making it impossible to properly tune such networks."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "id": "IbTQVeEueUps"
   },
   "source": [
    "The hyperbolic tangent or $\\text{tanh}$ activation introduced in Section 6.2.2, being defined in terms of the logistic sigmoid, can similarly suffer from the vanishing gradient problem even though it typically performs considerably better in practice, perhaps because it centers its output about the origin."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {
    "id": "YMDdlLEFeUps",
    "outputId": "8f8395fa-4449-41dc-9427-ce55888a053d"
   },
   "outputs": [
    {
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",
      "text/plain": [
       "<Figure size 800x500 with 4 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "def activation1(w):\n",
    "    a = 1/(1 + np.exp(-5*w))\n",
    "    return a\n",
    "\n",
    "def activation2(w):\n",
    "    a = np.maximum(0,w)\n",
    "    return a\n",
    "\n",
    "# create input and functions to plot\n",
    "w = np.linspace(-5,5,100)\n",
    "a = activation1(w)\n",
    "deg = 20\n",
    "# a2 = my_act(w)\n",
    "a2 = activation2(w)\n",
    "\n",
    "# create derivatives to plot\n",
    "der = grad(activation1)\n",
    "b = np.array([der(v) for v in w])\n",
    "der2 = grad(activation2)\n",
    "b2 =  np.array([der2(v) for v in w])\n",
    "\n",
    "### figure construction ###\n",
    "# initialize figure\n",
    "fig = plt.figure(figsize = (8,5))\n",
    "\n",
    "# create subplot with 1 panel\n",
    "gs = gridspec.GridSpec(2, 2) \n",
    "ax = plt.subplot(gs[0]); \n",
    "ax.plot(w,a);\n",
    "ax = plt.subplot(gs[1]); \n",
    "ax.plot(w,a2);\n",
    "\n",
    "ax = plt.subplot(gs[2]); \n",
    "ax.plot(w,b);\n",
    "ax = plt.subplot(gs[3]); \n",
    "ax.plot(w,b2);"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "id": "GNIeK6oeeUpt"
   },
   "source": [
    "#### <span style=\"color:#a50e3e;\">Example 2. </span>  The rectified linear unit (ReLU) activation"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "id": "xV7FELR5eUpt"
   },
   "source": [
    "For decades after the multi-layer perceptron was first introduced researchers employed logistic activation functions almost exclusively. Only recently (the early 2010s, often the act of breaking away from tradition is a far greater feat than besting any test of mental strength) were alternative activation functions popularly entertained and tested, with the simple ReLU function providing (in many cases, largely in the context of image-based problems) far superior results than sigmoid activations.\n",
    "\n",
    "A simpler function than a sigmoid (which involves both the use of a $\\text{log}$ and exponential function), the ReLU function (and its relatives) have quickly become the most popular activation functions in use today. Notice, the ReLU function (plotted in the top right panel of Figure above) does not suffer from the same sort of vanishing gradient problem that the sigmoid does, as its derivative (plotted in the lower right panel of Figure above) only maps negative values to zero. However some care still must be taken when initializing and training a network employing ReLU activations. For example, akin to the need to initialize the ReLU cost function detailed in Section 6.3.1 away from the origin where the optimization process will stall, a multi-layer perceptron employing ReLU activations should be initialized away from the origin to avoid too many of the units (and their gradients) from vanishing."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "id": "8yIwv5iDeUpu"
   },
   "source": [
    "#### <span style=\"color:#a50e3e;\">Example 3. </span>  The maxout activation"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "id": "I6WViltieUpu"
   },
   "source": [
    "The *maxout* activation, defined as\n",
    "\n",
    "\\begin{equation}\n",
    "a(x) = \\text{max}(v_0 + v_1x, \\,w_0 + w_1x) \\\\\n",
    "\\end{equation}\n",
    "\n",
    "is a relative of the ReLU that takes the maximum of two linear combinations of the input (instead of one linear combination and zero, as is the case with ReLU). Four instances of such a maxout unit are plotted below, in each instance its parameters are chosen at random. While this change seems algebraically rather minor, multi-layer perceptron architectures employing the maxout activation tend to have certain advantages over those employing $\\text{tanh}$ and ReLU activations, including 1) fewer issues with problematic initialization (e.g., values close to or equal to zero for the *ReLU* activation are bad because the relu is minimized at zero), 2) fewer issues with gradients vanishing, and 3) empirically faster convergence with far fewer gradient descent steps. These advantages come with a simple price: the maxout activation has twice as many internal parameters as either the ReLU or $\\text{tanh}$, hence architectures built with them have roughly twice as many parameters to tune."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {
    "id": "NzpSoTvteUpu",
    "outputId": "59fbaa58-9e7f-4fee-86f2-049b2a60ad5b"
   },
   "outputs": [
    {
     "data": {
      "image/png": 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    "<a id='bib_cell'></a>\n",
    "\n",
    "## References\n",
    "\n",
    "[1]  W. S. McCulloch and W. Pitts. A logical calculus of the ideas immanent in nervous activity. The bulletin of mathematical biophysics, 5(4):115–133, 1943.\n",
    "\n",
    "[2]  D. O. Hebb. The organization of behavior: a neuropsychological theory. John Wiley & Sons, New York, 1949.\n",
    "\n",
    "[3]  F. Rosenblatt. The perceptron - a perceiving and recognizing automaton. Cornell Aeronautical Laboratory, 1957.\n",
    "\n",
    "[4]  B. Merker. From probabilities to percepts: a subcortical \"global best estimate buffer\" as locus of phenomenal experience\". In: S. Edelman, T. Fekete and N. Zach (Eds.) Being in time: Dynamical models of phenomenal experience. (pp. 37–79). John Benjamins Publishing Company, Amsterdam, 2012."
   ]
  }
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